Loading...

Integration of image de-blurring in an aerial Mono-SLAM

Atashgah, M. A. A ; Sharif University of Technology

480 Viewed
  1. Type of Document: Article
  2. DOI: 10.1177/0954410013491663
  3. Abstract:
  4. In this article, we discuss the possibility of integrating image de-blurring techniques in an aerial simultaneous localization and mapping by a single camera (monocular simultaneous localization and mapping (Mono-SLAM)). We use an integrated aerial virtual environment together with a six-degree-of-freedom aircraft flight simulator to show the effectiveness of the approach to generate three-dimensional flight trajectories via integration of image de-blurring in the associated loop of the Mono-SLAM. The objective is to increase the overall performance of a flying mission over an unknown area by means of a vision-only method. The integrated aerial virtual environment produces and collects real-time pictures from a nadir-looking vision sensor mounted on the vehicle. Our MATLAB GUI-based toolbox helps user to investigate an offline Mono-SLAM with a predefined de-blurring method integrated with an estimator which extracts navigational parameters. The system efficient architecture allows effective virtual experiments in a completely unknown environment, without using preloaded maps or predefined features. Simulation outcomes demonstrate the feasibility of navigation of aerial robots in inaccessible environments. Different case studies support the conclusion; nonetheless, we observe a number of nonlinearities from de-blurring filters even for a general aviation aircraft
  5. Keywords:
  6. De-blurring in-the-loop SLAM ; Mathematical techniques ; MATLAB ; Navigation ; Robots ; Virtual reality ; Aerial navigation ; Deblurring ; Flight simulation ; Image deblurring ; Monocular SLAM
  7. Source: Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering ; Vol. 228, issue. 8 , May , 2014 , p. 1348-1362
  8. URL: http://pig.sagepub.com/content/early/2013/06/17/0954410013491663